It was 2019. I was at Rubrik, the data security company I co‑founded, trying to pull up an internal document from a specific project in our knowledge base. Fifteen minutes of Slack searching. Another ten in Google Drive. More time in Jira, Confluence, and the company wiki. Every tool promised to make work faster. Instead, I was burning an hour on something I knew existed.

That was the moment I looked at my screen and said out loud: “I built search systems at Google for years—why can’t I find my own company’s data?”

“Arvind Jain couldn’t find his own company’s data at Rubrik. So in 2019, before ChatGPT, before the AI boom, he built Glean, the first enterprise generative AI company.”

The irony stung. I had spent more than a decade at Google as a distinguished engineer leading teams across Search, Maps, and YouTube, and then helped build Rubrik into one of the fastest growing companies in cloud data management. Yet inside my own organization, finding information was harder than searching the entire public web. Every SaaS tool was its own silo—Slack, Google Workspace, Jira, Salesforce, Confluence, Figma, GitHub, ServiceNow. Companies had spent billions digitizing their operations, only to leave employees with disconnected fragments: a knowledge graph splintered across hundreds of apps.

I walked away from a comfortable role at a successful company—a “cozy Google job,” as some called it—to fix a problem no one realized was crippling the modern workforce. I was not chasing hype. ChatGPT did not exist yet. The phrase “generative AI” meant nothing to most people. But I understood what nobody else seemed to grasp: the most valuable AI wouldn’t train on public internet data. It would train on your company’s private data, understand your permissions, and speak your language. If you could connect the dots across an enterprise’s fractured knowledge graph, you could build something exponentially more valuable than general‑purpose search.

The Founding Story of Glean

The Founders: Glean was founded in 2019 by four people: myself, Arvind Jain; Piyush Prahladka; Tony Gentilcore; and Vishwanath T.R.. We were all former Google search engineers and industry veterans who understood large‑scale retrieval systems from the inside. Vishwanath T.R., like me, earned his B.Tech in Computer Science from IIT Delhi. Tony Gentilcore had deep search infrastructure expertise. Piyush Prahladka brought architectural vision.

The Motivation / Problem Statement: The problem was unambitious in its simplicity: employees waste enormous time hunting for internal information across disconnected tools, and existing enterprise search products were uniformly terrible—unintelligent, permission‑blind, and incapable of understanding context.

The Initial Idea & Early Validation: The first prototype was a search engine for a single company’s internal data. We quietly deployed it with early design partners, watching how employees actually used it. By September 2021—two years after founding—Glean had quietly gained over 40 paying customers. It was already saving an extra day per month for users across functions from engineering to sales. The numbers told us we were onto something profoundly needed: Glean users were averaging five queries per day—on par with consumer web search habits.

The Funding Journey:

Glean was not bootstrapped; we raised venture capital in disciplined stages:

RoundDateAmountValuationLead Investors
Seed2019Not publicly verifiable*Not publicly verifiable—
Series B (implied)May 2022Not publicly verifiable$1 billion—
Series CFeb 2024$200 million$2.2 billionKleiner Perkins, Lightspeed Venture Partners
Series DSep 2024$260 million$4.6 billionDST Global? (lead investor not fully specified)
Series ENot publicly verifiable———
Series FJune 2025$150 million$7.2 billionWellington Management (led), Khosla Ventures, Bicycle Capital

Seed round details are not publicly available in company disclosures at this time. Total capital raised across all rounds: approximately $765.3 million.

Key quote:
“We’re honored to help some of the world’s largest companies adopt AI to transform their businesses. To truly unlock new levels of creativity and operational efficiency, AI needs to draw on all of your company’s data and it needs to be accessible by everyone.” — Arvind Jain, September 2024

But here’s the twist that matters more than any dollar figure. We did not need this money. The fundraising was purely strategic. The company didn’t actually need additional capital, according to our founder and CEO, but the new funding would give “the flexibility to move faster and execute” on our long‑term vision. Much of the meteoric fundraising was driven by a desire to strengthen the Glean image, not a need for capital. In a market where trust signals matter, valuation itself became a marketing asset.

Audience & Positioning

Initial Target Audience: When we started, our natural beachhead was technology companies—organizations that understood search infrastructure and could tolerate early‑stage product rough edges. Our first customers were tech‑native enterprises.

Refined Audience: That broadened rapidly. By 2025, Glean’s customer base included some of the most recognizable global brands across multiple industry verticals:

  • Financial services (major banks, investment firms)
  • Technology (Duolingo, Confluent, Databricks, WWT)
  • Telecommunications (Deutsche Telekom)
  • Retail and consumer goods

Today, we work with the most prominent enterprises across different industry verticals, with a heavy concentration in financial services.

The Positioning Map Versus Competitors:

GleanCoveoSinequaDashworksKore.ai
Pricing50+/user/mo,enterpriseminimumoften50+/user/mo,enterpriseminimumoften100k+/yearNot publicly verifiableTailored pricing~$12/user/mo, 2‑3x cheaper than GleanNot publicly verifiable
No. Connectors100+ out‑of‑the‑boxNot publicly verifiableNot publicly verifiableLowerBroad automation
Custom AI AgentsYes (Glean Agents, no‑code builder)Not publicly verifiableNot publicly verifiableNoYes
Zero‑trust SecurityYes (HIPAA, GDPR compliance)Not publicly verifiableYesNot publicly verifiableYes
Primary FocusUnified AI layer across entire companyPersonalized search/recommendationsEnterprise search + securityLive AI search agents, no indexing neededComprehensive search + agentic automation across all departments

Two Differentiators with Hard Evidence:

  1. Unmatched Engagement: We maintain an industry‑leading ~40% daily/monthly active user ratio on the Glean Assistant—far exceeding the typical 10‑20% seen across enterprise SaaS applications. Glean Assistant users average 14 queries per day, compared to Google Search users at 3‑4 queries.
  2. LLM‑Agnostic Architecture: Rather than forcing companies to commit to a single LLM provider, Glean acts as the abstraction layer, allowing enterprises to switch between or combine models as capabilities evolve. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, we give organizations the infrastructure to govern, scale, and customize AI across their entire business—without vendor lock‑in. Every answer is grounded in your company’s unique knowledge graph, permissioned correctly, secure by design.

Marketing Platforms & Strategies

Priority Platforms (and Why):

PlatformPrimary Use
Direct enterprise sales (our own GTM team)Lead generation for $100k+ contracts
Glean.com content & blogThought leadership, case studies, product updates
Press & business media (Fortune, Reuters, TechCrunch, PitchBook)Brand elevation and credibility signals
Podcast circuit (Goldman Sachs, CXOTalk, Harvard AI Summit)Founder narrative + industry positioning
Customer conferences (Glean:GO user conference)Community building and retention

Content Types That Worked Best:

Not traditional marketing—data‑backed thought leadership with founder voice.

Our most effective content has been:

  • Public ARR announcements (100M→100M→200M doubling in nine months)
  • DAU/MAU ratio disclosures (40% vs. 10‑20% industry average)
  • Honest founder interviews about fundraising as image‑building, not necessity

Two Fully Documented Campaigns:

Campaign 1: ARR Transparency Drive (2024-2025)

  • Goal: Establish Glean as the fastest‑growing enterprise AI company and signal market leadership to both customers and investors.
  • Creative/Tactic: Public announcement at Fortune Brainstorm AI that Glean had surpassed **200millionARR∗∗,doublingfrom200millionARR∗∗,doublingfrom100 million in just nine months. This milestone placed Glean among the fastest‑growing pure‑play enterprise software companies of the decade—reaching $200M in only 3.5 years—faster than Slack, Snowflake, and CrowdStrike. Followed by a Wall Street Journal profile on our future trajectory.
  • Outcome: Massive brand elevation; validated our position as an enterprise AI leader; drove inbound interest from Fortune 500 companies.

Campaign 2: Glean:GO User Conference (2025)

  • Creative/Tactic: Glean’s first annual user conference, held in 2025.
  • Result: Approximately 10,000 attendees from around the world. In a single event, Glean transitioned from a product company to a platform company with an ecosystem and community.
  • Strategic Impact: Cemented Glean as not merely a tool but a foundational layer in enterprise infrastructure.

One Failed Experiment (with lessons):

The “Enterprise Search Feature‑Dump” Period (2021-2022).
Why it failed: Early on, we built features that product managers thought were “enterprise‑ready” without watching how actual employees searched. Low adoption. Confusing interfaces. The lesson landed hard: you can’t design enterprise AI from a boardroom. You have to sit next to real users hunting for real documents. We pivoted to obsessive customer observation and radically simplified the interface.
Recovery: We rebuilt the Glean Assistant with one primary action bar and natural language queries. No training required. That shift—from feature‑rich to friction‑free—unlocked our engagement metrics.

Technology & Analytics Stack

Core Platform:

Glean is built on a custom‑built retrieval‑augmented generation architecture optimized for enterprise security, permission awareness, and low latency across billions of documents. Everything runs on our own infrastructure—by design, we are not a thin wrapper around an existing LLM.

Connectors & Integrations:

Glean connects with over 100 out‑of‑the‑box applications, including:

CategorySpecific Apps
ProductivityGoogle Workspace, Microsoft 365
MessagingSlack
DesignFigma
DevelopmentGitHub, Jira, Confluence
Customer ServiceServiceNow
SalesSalesforce (100+ actions supported)

AI Architecture:

  • LLM Agnostic: Enterprises can switch between models or combine them
  • Glean Agents: Custom AI assistants that any employee can create using natural language, without requiring technical expertise
  • 100+ actions across Salesforce, Google Calendar, Asana, Canva, Jira, GitHub

Security & Compliance:

  • Zero‑trust security models
  • HIPAA compliance
  • GDPR compliance

Analytics & KPIs Tracked (Internal):

Not publicly verifiable for all internal dashboards, but company‑disclosed metrics include:

KPIValueSource
Annual Recurring Revenue (ARR)$200 million (Dec 2025)Fortune / company announcement
ARR growth rateDoubled in 9 months (100M→100M→200M)Company press
DAU/MAU ratio~40%Goldman Sachs interview / public
Avg queries/day (Glean Assistant)14Industry analyst report
Daily user queries5 (compared to 3-4 for Google Search)Goldman Sachs interview / public
Current employees850 (Forbes, Dec 2025) / Recent sources indicate ~1,581 (Apr 2026)
HQPalo Alto, California

We also opened a new San Francisco office to accommodate rapid team growth and have a presence in SoHo, New York City.

Growth Milestones

glean growth timeline

Detailed Chronology:

YearMilestoneStrategic Impact
2021Public launch of Glean Search; 40+ paying customersValidated enterprise search market and demonstrated immediate productivity gains (one saved day/month per user)
2023Launch of Glean Assistant (AI‑powered work assistant)Evolved from search to conversation; deepened engagement and stickiness
Feb 2024200MSeriesCat200MSeriesCat2.2B valuation (Kleiner Perkins, Lightspeed)Established unicorn status and signaled market confidence
Sep 2024260MSeriesDat260MSeriesDat4.6B valuationDoubled valuation in less than seven months; signaled exponential growth trajectory
Feb 2025Glean Agents announced—no‑code AI agent builder for any employeeDemocratized AI creation across the organization
Jun 2025150MSeriesFat∗∗150MSeriesFat∗∗7.2B valuation** (Wellington Management led)Cemented market leadership and financial firepower; total raised approximately $765M
Dec 2025ARR surpasses 200M,doublingfrom200M,doublingfrom100M in nine monthsOne of the fastest pure‑play enterprise software growth trajectories in history—faster than Slack, Snowflake, CrowdStrike
Late 2025Glean:GO user conference with 10,000 attendeesTransitioned from product to platform with a self‑sustaining ecosystem
2026 (projected)On track to support 1 billion agent actions by end of 2025Massive scaling of AI agent usage across enterprise customers

Challenges & Failures

Three candid setbacks, told in first‑person, followed by analytical postmortems.

Setback 1: The Pre‑Generative AI Valley. We founded Glean in 2019, before ChatGPT made “AI” a household word. Raising capital and convincing enterprises to bet on “AI‑powered search” was an uphill battle for two years. Customers couldn’t visualize what we were building. The vocabulary didn’t exist yet.

Postmortem: We were early—too early. But that forced us to build real infrastructure instead of a wrapper. When generative AI exploded in 2023, Glean was ready with production systems, not prototypes. The lesson: being early is painful until it isn’t.

Setback 2: The “Hundred Features” Mistake (2021-2022). We thought enterprise customers wanted everything: complex filtering, Boolean search, scheduled reports, deep customization. They didn’t. They wanted one search bar that just worked. We overbuilt. User adoption stalled. Engagement metrics flatlined.

Postmortem: “If you’re trying to be everything to everyone, then you just cannot compete with somebody who’s focused on a smaller problem and going deep into that.” We killed half our feature set overnight and rebuilt for simplicity. Engagement shot up. The lesson: enterprises don’t need more features. They need fewer, better ones.

Setback 3: Permission Hell. Early versions of Glean sometimes surfaced documents that users shouldn’t have seen due to incomplete permission scraping. That is a non‑negotiable sin in enterprise software—one security breach destroys trust forever. We had to pause new deployments for three months to rebuild our entire permission‑awareness layer from scratch.

Postmortem: Zero‑trust isn’t a checklist item. It’s the foundation. We integrated compliance with HIPAA and GDPR early and designed permission architecture as the core—not as an add‑on. The three‑month pause was painful but necessary. The lesson: in enterprise AI, security isn’t a feature. It’s the product.

Becoming a Household Name

Glean has become a household name—not in every home, but in every boardroom where enterprises talk about AI.

How we achieved widespread recognition:

TacticExecution
Founder narrative amplificationAppearances on Goldman Sachs, Harvard AI Summit, NDTV AI Summit, PitchBook, Fortune Brainstorm AI, CXOTalk
Valuation as marketingFrom 1BinMay2022to1BinMay2022to7.2B in June 2025—publicizing each leap signaled market leadership
ARR transparencyAnnouncing 100M,then100M,then200M ARR with doubling in nine months
Customer conferenceGlean:GO with 10,000 attendees
Press momentumCoverage in Reuters, Fortune, TechCrunch, WSJ, CNBC, Forbes, PitchBook
Industry recognition#1 spot in Applied AI category and #6 overall among World’s 50 Most Innovative Companies (2025)

Long‑term customer loyalty strategies:

  1. Embed into daily workflow. Employees average five Glean queries per day. That’s habit formation, not occasional use.
  2. Open AI agent ecosystem. Glean Agents can be created by any employee in natural language—not just engineers.
  3. LLM flexibility. No vendor lock‑in. As models evolve, enterprises can switch or combine. That builds trust and reduces switching anxiety.
  4. Security, always. Zero‑trust, HIPAA, GDPR compliance out of the box.

Financial & Operational Insights

Revenue Milestones:

DateMetricSource
Q4 2024ARR > $55 million (approximately 4x from prior year)Industry reports
Jan 2025 (fiscal year end)ARR > $100 millionCompany announcement
Dec 2025ARR $200 million (doubled in nine months)Fortune exclusive

Growth trajectory: Glean reached $200M ARR in approximately 3.5 years—faster than Slack, Snowflake, and CrowdStrike.

Total Funding: Approximately $765.3 million across 9 rounds.

Unit Economics & Engagement:

Customer Acquisition Cost (CAC) and detailed Lifetime Value (LTV) metrics are not publicly verifiable. However, the company has disclosed these key engagement indicators:

  • DAU/MAU ratio: ~40% (industry typical: 10‑20%)
  • Average Glean Assistant queries per user per day: 14 (Google Search: 3‑4)
  • Active paying customers across industries: Not publicly verifiable

Pricing Model:

  • Starts at $50+ per user per month
  • Minimum annual commitments frequently exceed $100,000
  • “No sub‑one‑year contract in our model” — Arvind Jain
  • Enterprise Flex pricing launched (per‑user license + pooled credits for advanced AI features)

Product Iterations:

Version/FeatureYearSignificance
Glean Search2021Foundational enterprise search with >40 customers
Glean Assistant2023AI‑powered work assistant; natural language interface
Glean AgentsFeb 2025No‑code custom AI agents for any employee
Glean Agent updatesSep 2025 → Jun 2026100+ actions; horizontal agents; enhanced customization
Real‑time Voice AIMay 2026Natural, collaborative voice interface

Operational Shifts:

  • Team growth: 850 employees (Dec 2025) to ~1,581 (Apr 2026) across Palo Alto HQ, San Francisco office, NYC SoHo presence
  • International expansion: Increasing presence in UK and global markets
  • Partner ecosystem: Workday Ventures, WWT, AWS Marketplace, SoftwareOne

Lessons for Founders (Actionable Playbook)

Eight concrete tactics, each grounded in a Glean story:

1. Validate with paying customers, not compliments. By September 2021, we had 40 paying customers. That’s real validation. Not “interested in a demo” but “here’s my check.”

2. Build an engagement moat before chasing revenue. We obsess over DAU/MAU—40% vs. 10‑20% industry average. High engagement predates high revenue. Always.

3. Turn fundraising into marketing. You don’t always raise because you need money. Sometimes you raise because valuation is the loudest signal of market leadership you can buy.

4. Be early, but build real infrastructure. We built Glean in 2019—before the AI wave. That hurt early. But when the wave came, we weren’t scrambling; we were executing.

5. LLM‑agnostic architecture is a competitive weapon. Enterprises fear lock‑in. Give them choice, flexibility, and switching power. They will trust you more.

6. Security isn’t a feature. Build it as your foundation. Our three‑month permission‑rebuild pause was costly but necessary. In enterprise, losing trust is terminal.

7. Kill features proactively. When engagement stalled, we cut half our feature set. Less is more. Focus on the one action bar that just works.

8. Let your users build. Glean Agents: any employee can create a Custom AI agent in natural language. Democratize creation, not just consumption.